Cartography Checklists

Last updated on 2026-03-27 | Edit this page

Overview

Questions

  • Who is the primary audience for your map?
  • What message or story are you trying to communicate?
  • Which data attributes are most important to show?
  • How will your audience interpret or react to your map?
  • What medium will your map be presented in (web, print, presentation)?
  • Will your map be used to inform decisions?
  • What does your audience already know, and what do they need explained?
  • Do you need more data to support your map?
  • Do you fully understand the topic you are mapping?

Objectives

  • Identify the purpose and audience of a map
  • Choose appropriate data and variables to visualize
  • Design maps that communicate clearly and accurately
  • Evaluate whether additional data or research is needed
  • Apply a checklist-based approach to cartographic design

Why Thoughtful Map Design Matters

Maps are powerful tools for communication. A well-designed map can reveal patterns, support decisions, and tell compelling stories. A poorly designed map can mislead, confuse, or hide important insights

Before making a map, it’s essential to ask the right questions. Good cartography follows core design principles:

  • legibility (easy to read)
  • visual contrast (important elements stand out)
  • figure-ground (main features pop from the background)
  • hierarchy (what’s most important first)
  • balance (pleasing layout without clutter)

1. Know Your Audience

Your audience determines everything about your map.

Ask yourself:

  • Are they experts, policymakers, or the general public?
  • What is their familiarity with maps and your topic?
  • What level of detail is appropriate?

Example:

  • General audience → simple labels, clear legend, minimal jargon
  • Scientific audience → more detail, precise scales, technical terminology
Callout

Key Idea

A map for scientists and a map for the public should not look the same.

2. Define Your Message

Every map should answer a clear question.

Ask yourself:

  • What is the single most important takeaway?
  • Are you showing patterns, comparisons, or changes over time?

Avoid:

  • Trying to show too many variables at once
  • Making the user “figure it out” without guidance

Good Example:

“This map shows areas at highest risk of flooding.”

Flood-Risk USA Map
Flood-Risk USA Map

3. Choose the Right Data Attributes

Not all data belongs on your map. Select variables that support your message and are spatially meaningful.

Ask yourself:

  • Which variable is most important?
  • Are there supporting variables (e.g., population, elevation)?
  • Is your data spatially appropriate (points, lines, polygons)?

Tips:

  • Use color for magnitude (e.g., rainfall)
  • Use size for comparison (e.g., population)
  • Use symbols for categories (e.g., land use)
Discussion

Quick Check

You have temperature, precipitation, and elevation data.
Which one would you prioritize if your goal is to show drought risk?

4. Consider Audience Perception

Maps are not neutral — design choices influence interpretation.

Ask yourself:

  • Could colors be misleading (e.g., red = danger)?
  • Are you introducing bias unintentionally?
  • Is the map easy to interpret at a glance?

Example:

  • Darker/Very Light colors may imply higher value and importance
  • Certain color schemes may exclude colorblind users (see next module)
Bad USA Map
Bad USA Map

Best Practice: Establish clear contrast between foreground (data) and background (basemap). Use figure-ground techniques, such as subtle vignettes or lighter basemaps, so your data stands out.

5. Choose the Right Medium

Where your map is displayed affects design decisions.

Common mediums:

  • Web maps → interactive, zoomable
  • Print maps → static, high resolution
  • Presentations → simple, bold visuals

Ask yourself:

  • Will users zoom in?
  • Will the map be printed in black and white?
  • How large will it appear?

Tip for Web: Simplify basemaps and use halos on labels for readability over varied backgrounds. For print, test a physical proof.

6. Will Your Map Inform Decisions?

Some maps are purely exploratory, while others guide real-world actions.

Decision-making maps should:

  • Be highly accurate
  • Include uncertainty (if possible)
  • Avoid misleading simplifications

Example:

  • Flood risk maps used by city planners
  • Public health maps used during outbreaks
Callout

Important

If your map influences decisions, accuracy and clarity are critical.

7. Understand Your Audience’s Knowledge

Ask yourself:

  • Do they understand your variables?
  • Do you need to explain units or scales?
  • Should you include annotations or context?

Tips:

  • Add legends and labels
  • Use plain language when possible
  • Provide context (e.g., time period, data source)
  • Include essential map elements: scale bar (when distance matters), north arrow (if orientation isn’t standard), and source citation

Pro Tip: Aim for “maximum information at minimum effort” — the viewer should grasp the main idea quickly without struggling.

8. Do You Need More Data?

Incomplete data can lead to misleading maps.

Ask yourself:

  • Are there missing variables that affect interpretation?
  • Is your data up to date?
  • Is the spatial resolution sufficient?

Example:

Mapping income without population density may mislead conclusions.

This is a good map but needs supporting information to better understand this distribution of income across the country. Green here indicates higher income.
This is a good map but needs supporting information to better understand this distribution of income across the country. Green here indicates higher income.
This population density map is in positive correlation with the map. As in, a higher population density would ideally mean a greater household income in that county. Lighter colors indicate greater population density.
This population density map is in positive correlation with the map. As in, a higher population density would ideally mean a greater household income in that county. Lighter colors indicate greater population density.

9. Do You Understand Your Data?

Before mapping, you should fully understand your dataset.

Ask yourself:

  • What does each variable represent?
  • Are there biases or limitations?
  • Have you explored the data (e.g., summary statistics)?

If not:

  • Perform exploratory data analysis (EDA)
  • Read metadata and documentation
  • Consult someone if needed
  • Research about the data more online!
  • Advanced: Conduct sensitivity tests as in, do the results change under different assumptions?

Cartography Checklist (Summary)

Before finalizing your map, review this checklist:

Final Thought

A good map is not just visually appealing — it is honest, clear, and purposeful. It respects the data, serves the audience, and communicates effectively without distortion.

Discussion

  • Think of a map you’ve seen recently.
    What did it do well? What could be improved?

  • How might the same data be presented differently for another audience?

  • Share an example of a map that misled you (or succeeded brilliantly) and why.